Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/easingthemes/dx-aem-flownpx agentmods add skills/easingthemes/dx-aem-flow/auto-alarmsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/easingthemes/dx-aem-flow/auto-alarms)<a href="https://agentmods.dev/skills/easingthemes/dx-aem-flow/auto-alarms"><img src="https://agentmods.dev/badge/skills/easingthemes/dx-aem-flow/auto-alarms/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/easingthemes/dx-aem-flow/auto-alarms"><img src="https://agentmods.dev/badge/skills/easingthemes/dx-aem-flow/auto-alarms.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00059 | $0.01236 |
| Opus 5 | $0.00030 | $0.00618 |
| Sonnet 5 | $0.00012 | $0.00247 |
| Haiku 4.5 | $0.00006 | $0.00124 |
Grade A, and why
auto-alarms scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You create CloudWatch alarms and subscribe an email address to alerts. Wraps lambda/cloudwatch/setup-alarms.sh with audit logging.
0. Prerequisites
Read .ai/automation/infra.json. Check automationProfile:
- If
consumer(or legacypr-only/pr-delegation): "This repo uses the consumer profile — CloudWatch alarms are managed by the hub project. Do NOT configure alarms from this repo." STOP.
source .ai/lib/audit.sh
export AUDIT_LOG_PREFIX=infra
Confirm monitoring config from infra.json:
monitoring.snsTopic.name— SNS topic name (<prefix>-alerts)region
1. Collect Email
If user passed --email <address>, use it. Otherwise ask:
Alert email address? CloudWatch alarms will notify this email for DLQ depth, Lambda errors, and throttles. You'll need to confirm the subscription in your email.
2. Run Setup Script
cd .ai/automation
bash lambda/cloudwatch/setup-alarms.sh --email "<email>"
The script:
- Creates the SNS topic
<prefix>-alerts(idempotent) - Subscribes the email to the topic
- Creates 4 CloudWatch alarms (reads definitions from
lambda/cloudwatch/alarms.json, prefixes with resource prefix frominfra.json) - Links each alarm to the SNS topic
Report the script's output.
3. Update infra.json
After the script runs, the SNS topic ARN is returned. Update infra.json:
monitoring.snsTopic.arn→ the created/retrieved ARN
4. Summary Report
## CloudWatch Monitoring Configured
**SNS topic:** <prefix>-alerts
**Alert email:** <email> (confirm subscription in your inbox)
| Alarm | Trigger | Severity |
|-------|---------|----------|
| <prefix>-dlq-depth | DLQ > 5 messages | Warning |
| <prefix>-lambda-errors-wi-router | WI-Router Lambda errors > 3/hour | Critical |
| <prefix>-lambda-errors-pr-router | PR-Router Lambda errors > 3/hour | Critical |
| <prefix>-lambda-throttles | Any Lambda throttled | Warning |
**infra.json** updated with SNS ARN.
**Audit log:** `.ai/logs/infra.<week>.jsonl`
### Next step
`/auto-test --dryRun` — Verify end-to-end (local dry run)
### Operational commands
- `/auto-status` — Current DLQ depth, token budget, rate limits
- `/auto-doctor` — Full health check
- See `docs/runbook.md` for alert response procedures
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 110 lines · 59 tokens per session scan A dc07f9669f7c
auto-alarms is a skill published in the GitHub repository easingthemes/dx-aem-flow (6 stars, last pushed 7d ago), licensed MIT. It adds 59 tokens to every session and 1,236 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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